Browsing by Author "Gajendra Kumar"

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Assessing population diversity and compositional structure in forests in Pachmarhi Biosphere Reserve, Central India
(Ecological Society of China, 2024) Gajendra Kumar; Amit Kumar; Purabi Saikia; M.L. Khan
The escalating impact of anthropogenic and climatic forces on forest bioresources poses significant challenges to the effective implementation of forest management plans, necessitating rigorous field investigations to provide the precise data required for developing effective conservation policies and ensuring ecosystem stability. This study addresses this need by presenting a comprehensive, field-based baseline framework that evaluates the effects of anthropogenic disturbances on floristic composition, tree diversity, and regeneration dynamics across tropical deciduous forest patches in Central India. Using a stratified random sampling approach with belt transects in 62 sites (0.5 ha each), the research documents 190 plant species, including 85 trees, 23 shrubs, and 82 herbs, with 37.89% listed on the IUCN Red-List, underscoring their conservation significance in Pachmarhi Biosphere Reserve (PBR). The findings reveal moderate tree density in the forests (386 individuals per hectare) dominated by Chloroxylon swietenia, and statistically significant correlations between disturbance index and biodiversity metrics including indices of diversity (H′), dominance (CD), evenness (E) and richness i.e., Dmg and Dmn. The study highlights a concerning trend of either poor or no regeneration in 67% of tree species in PBR, linked to increasing anthropogenic pressures such as logging and fuelwood collection. The study also recorded 737 cut stumps across 45 forest patches (72.58%), with a disturbance index of 5.54, signaling an urgent need for conservation interventions. This research provides critical baseline data on the floristic composition and species richness of these forests, offering valuable insights for developing effective management strategies. Sustainable biodiversity management in the Biosphere Reserve requires targeted rehabilitation, protection, and intensive regeneration efforts to preserve this ecologically rich yet vulnerable ecosystem. © 2024 Ecological Society of China
Assessing the accuracy of different Z-R relationships for Doppler Weather Radar based rainfall estimation: A comparative study for the Delhi region
(Elsevier Ltd, 2025) J. Sharma; Arpita Rastogi; Shikha Verma; Gajendra Kumar; Arti K. Choudhary
Z-R relationships are the most used methods for calculating rainfall using radar reflectivity, which provide a relation between the radar reflectivity (Z) to rainfall rate (R). However, different Z-R relationships may yield varying rainfall estimates depending on regional climatic conditions and radar characteristics. This study presents a comparison of various Z-R relationships (Marshall-Palmer (Z = 200R1.6), WSR-88D (Z = 300R1.4), and Rosenfeld tropical (Z = 250R1.2)) for the Delhi radar station for 2019. The study was performed for four seasons (Winter, Pre-Monsoon, Monsoon, and Post-monsoon) as well as for different rainfall intensity (Light, Moderate, and Heavy rain). The accuracy of each relationship was evaluated using statistical variables such as correlation coefficient (R), RMSE, MAE, Bias and NSE. Results indicate significant variability in rainfall estimation across different relationships. The Marshall-Palmer encompasses the best correlation with rain gauge data during the monsoon and post-monsoon, whereas the Rosenfeld Tropical exhibits the strongest correlation for the winter and pre-monsoon. Additionally, Rosenfeld Tropical has a strong correlation for moderate and heavy rainfall intensity, whereas Marshall Palmer offers a satisfactory correlation for light rainfall intensity. However, Marshall-Palmer offers the best performance for the overall dataset with R = 0.623, RMSE of 13.44, and MAE = 10.07, as well as the lowest RMSE for all seasons and rainfall intensity. These findings highlight the significance of selecting a correct Z-R relationship for accurate rainfall estimation in diverse meteorological conditions, and underscore the need for localized calibration of Z-R parameters for enhanced forecasting accuracy in the Delhi region. © 2025 Elsevier Ltd.
Effect of unusual dust event on meteorological parameters & aerosol optical and radiative properties
(India Meteorological Department, 2018) V.K. Soni; Sanjay Bist; R. Bhatla; S.C. Bhan; Gajendra Kumar; M. Sateesh; Siddhartha Singh; D.R. Pattanaik
A very unusual dust plume generated from dust-storm activities over the Arabian Peninsula and Southwest Asia affected the north-west region of India between March 20 and 23, 2012, causing significant reductions in air quality and consequently changes in meteorological parameters. Ground based measurements of aerosol optical depth at 500 nm reached 1.015 ± 0.24 and 0.837 ± 0.042 at Jodhpur while Angstrom exponent dropped to-0.030 and-0.065 on March 20 and 21, 2012 respectively. The AOD reached 0.959 in Delhi while Angstrom exponent dropped to 0.006 on March 21, 2012. PM10 concentration peaked at an unusually high value of more than 1800 μgm-3 during dust storm hours of March 20, 2012 at Delhi. Moderate Resolution Imaging Spectrometer (MODIS) retrieved aerosol optical depth also exhibited high values as well along the path of dust storm and dust plume. The intensity of the dust plume was such that it caused significant cooling at the surface. The large reduction in the radiative flux at the surface level had caused a drop in surface temperature by approximately 2-10 °C. Shortwave and longwave Direct Aerosol Radiative Forcing was calculated using SBDART during the dust period. © 2018, India Meteorological Department. All rights reserved.
Forest monitoring tools and techniques with special emphasis on tropical forests
(Elsevier, 2025) Pawan Ekka; Gajendra Kumar; A. Naga Lakshman Kumar; Purabi Saikia
Environmental researchers and forest practitioners have been using different traditional and advanced methods for forest surveillance, field mapping, and integrated information. The growing concern of threats to natural forests by landscape change, habitat and biodiversity loss, and climate change has shifted the monitoring and ground-truthing efforts toward digitization by transforming data acquisitions, analysis, and integrated research and development methods. Forest management practices through “Digitalization of forest” is a new way of forest conservation, monitoring, and ground truthing in recent years, creating opportunities to improve assessments and monitoring activity. Remote sensing is an omnipresent operational technology increasingly used in forest monitoring by various stakeholders. Integration of Wireless Sensor Networks (WSN), Artificial Intelligence (AI), Mobile mapping, and Open Data Platforms (ODPs) are important monitoring tools and techniques used by ecologists and conservation scientists for decision-making, prediction models, and restoration activities. The present chapter briefly discusses traditional and advanced forest monitoring and ground-truthing tools and techniques used for data acquisition and analysis in research and development. It also overviews major challenges and recent progress to further find opportunities by stakeholders and practitioners for additional investigation, advancements in research, development, and technology innovation. © 2026 Elsevier Inc. All rights reserved..
Kolkata’s green oasis: a comprehensive analysis of urban green spaces for ecosystem sustainability
(Springer, 2025) Poushali Biswas; Amit Kumar; Manjari Upreti; Gajendra Kumar; Purabi Saikia
In the present study, the impact of urban growth on green spaces in Kolkata Metropolitan City (KMC) was evaluated using the multi-temporal satellite observations spanning the last four decades (1990–2022). The study exhibited a rapid rise in urban areas (178.38% growth; net increase 498 sq.km), leading to a significant conversion of areas into moderate to very high built-up density zones. This urbanization has markedly altered the green–blue infrastructure, notably causing a 27% decline in urban green space (UGS) resulting a net loss of 254 sq.km. Fragmentation analysis exhibited a trend of compact, infill development in urban regions, contrasting with outgrowth, which has influenced both the cluster size and quality of UGS over the decades. The multi-indices and biophysical characterization of UGS concluded a deteriorating trend in terms of quantity (− 27.9%) and quality as well with reference. However, the existing UGS are primarily scattered and having less dense. Spatial estimation of above ground biomass (AGB) of UGS using regression analysis of field-derived AGB and L-band SAR backscatter depicted a dominance of low AGB (< 30 t/ha−1) across KMC, while the certain zones with improved UGS exhibited moderate AGB levels (50–100 t/ha−1). The fuzzy AHP-based multi-criteria analysis of urban ecological quality exhibited severe ecological deterioration in the central urban areas, moderate to high in peri-urban regions, and comparatively improved ecological conditions in the peripheral rural parts of KMC. The study also identified major native tree species for plantation strategies comprising urban afforestation, rooftop gardens, and the development of green corridors in ecologically deficient hotspot zones to improve the ecological quality within the urban landscape. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.